Augmented reality and physical hybrid model simulation for preoperative planning of metopic craniosynostosis surgery.

OBJECTIVE: The main objective of neurosurgery is to establish safe and reliable surgical techniques. Medical technology has advanced during the 21st century, enabling the development of increasingly sophisticated tools for preoperative study that can be used by surgeons before performing surgery on an actual patient. Laser-printed models are a robust tool for improving surgical performance, planning an operative approach, and developing the skills and strategy to deal with uncommon and high-risk intraoperative difficulties. Practice with these models enhances the surgeon's understanding of 3D anatomy but has some limitations with regard to tactile perception. In this study, the authors aimed to develop a preoperative planning method that combines a hybrid model with augmented reality (AR) to enhance preparation for and planning of a specific surgical procedure, correction of metopic craniosynostosis, also known as trigonocephaly. METHODS: With the use of imaging data of an actual case patient who underwent surgical correction of metopic craniosynostosis, a physical hybrid model (for hands-on applications) and an AR app for a mobile device were created. The hybrid customized model was developed by using analysis of diagnostic CT imaging of a case patient with metopic craniosynostosis. Created from many different types of silicone, the physical model simulates anatomical conditions, allowing a multidisciplinary team to deal with different situations and to precisely determine the appropriate surgical approach. A real-time AR interface with the physical model was developed by using an AR app that enhances the anatomic aspects of the patient's skull. This method was used by 38 experienced surgeons (craniofacial plastic surgeons and neurosurgeons), who then responded to a questionnaire that evaluated the realism and utility of the hybrid AR simulation used in this method as a beneficial educational tool for teaching and preoperative planning in performing surgical metopic craniosynostosis correction. RESULTS: The authors developed a practice model for planning the surgical cranial remodeling used in the correction of metopic craniosynostosis. In the hybrid AR model, all aspects of the surgical procedure previously performed on the case patient were simulated: subcutaneous and subperiosteal dissection, skin incision, and skull remodeling with absorbable miniplates. The pre- and postoperative procedures were also carried out, which emphasizes the role of the AR app in the hybrid model. On the basis of the questionnaire, the hybrid AR tool was approved by the senior surgery team and considered adequate for educational purposes. Statistical analysis of the questionnaire responses also highlighted the potential for the use of the hybrid model in future applications. CONCLUSIONS: This new preoperative platform that combines physical and virtual models may represent an important method to improve multidisciplinary discussion in addition to being a powerful teaching tool. The hybrid model associated with the AR app provided an effective training environment, and it enhanced the teaching of surgical anatomy and operative strategies in a challenging neurosurgical procedure.

Patient-specific 3-dimensionally printed models for neurosurgical planning and education.

OBJECTIVE: Advances in 3-dimensional (3D) printing technology permit the rapid creation of detailed anatomical models. Integration of this technology into neurosurgical practice is still in its nascence, however. One potential application is to create models depicting neurosurgical pathology. The goal of this study was to assess the clinical value of patient-specific 3D printed models for neurosurgical planning and education. METHODS: The authors created life-sized, patient-specific models for 4 preoperative cases. Three of the cases involved adults (2 patients with petroclival meningioma and 1 with trigeminal neuralgia) and the remaining case involved a pediatric patient with craniopharyngioma. Models were derived from routine clinical imaging sequences and manufactured using commercially available software and hardware. RESULTS: Life-sized, 3D printed models depicting bony, vascular, and neural pathology relevant to each case were successfully manufactured. A variety of commercially available software and hardware were used to create and print each model from radiological sequences. The models for the adult cases were printed in separate pieces, which had to be painted by hand, and could be disassembled for detailed study, while the model for the pediatric case was printed as a single piece in separate-colored resins and could not be disassembled for study. Two of the models were used for patient education, and all were used for presurgical planning by the surgeon. CONCLUSIONS: Patient-specific 3D printed models are useful to neurosurgical practice. They may be used as a visualization aid for surgeons and patients, or for education of trainees.

Reliable navigation registration in cranial and spine surgery based on intraoperative computed tomography.

OBJECTIVE: Low registration errors are an important prerequisite for reliable navigation, independent of its use in cranial or spinal surgery. Regardless of whether navigation is used for trajectory alignment in biopsy or implant procedures, or for sophisticated augmented reality applications, all depend on a correct registration of patient space and image space. In contrast to fiducial, landmark, or surface matching-based registration, the application of intraoperative imaging allows user-independent automatic patient registration, which is less error prone. The authors' aim in this paper was to give an overview of their experience using intraoperative CT (iCT) scanning for automatic registration with a focus on registration accuracy and radiation exposure. METHODS: A total of 645 patients underwent iCT scanning with a 32-slice movable CT scanner in combination with navigation for trajectory alignment in biopsy and implantation procedures (n = 222) and for augmented reality (n = 437) in cranial and spine procedures (347 craniotomies and 42 transsphenoidal, 56 frameless stereotactic, 59 frame-based stereotactic, and 141 spinal procedures). The target registration error was measured using skin fiducials that were not part of the registration procedure. The effective dose was calculated by multiplying the dose length product with conversion factors. RESULTS: Among all 1281 iCT scans obtained, 1172 were used for automatic patient registration (645 initial registration scans and 527 repeat iCT scans). The overall mean target registration error was 0.86 ± 0.38 mm (± SD) (craniotomy, 0.88 ± 0.39 mm; transsphenoidal, 0.92 ± 0.39 mm; frameless, 0.74 ± 0.39 mm; frame-based, 0.84 ± 0.34 mm; and spinal, 0.80 ± 0.28 mm). Compared with standard diagnostic scans, a distinct reduction of the effective dose could be achieved using low-dose protocols for the initial registration scan with mean effective doses of 0.06 ± 0.04 mSv for cranial, 0.50 ± 0.09 mSv for cervical, 4.12 ± 2.13 mSv for thoracic, and 3.37 ± 0.93 mSv for lumbar scans without impeding registration accuracy. CONCLUSIONS: Reliable automatic patient registration can be achieved using iCT scanning. Low-dose protocols ensured a low radiation exposure for the patient. Low-dose scanning had no negative effect on navigation accuracy.

Augmented-reality integrated robotics in neurosurgery: are we there yet?

Surgical robots have captured the interest-if not the widespread acceptance-of spinal neurosurgeons. But successful innovation, scientific or commercial, requires the majority to adopt a new practice. "Faster, better, cheaper" products should in theory conquer the market, but often fail. The psychology of change is complex, and the "follow the leader" mentality, common in the field today, lends little trust to the process of disseminating new technology. Beyond product quality, timing has proven to be a key factor in the inception, design, and execution of new technologies. Although the first robotic surgery was performed in 1985, scant progress was seen until the era of minimally invasive surgery. This movement increased neurosurgeons' dependence on navigation and fluoroscopy, intensifying the drive for enhanced precision. Outside the field of medicine, various technology companies have made great progress in popularizing co-robots ("cobots"), augmented reality, and processor chips. This has helped to ease practicing surgeons into familiarity with and acceptance of these technologies. The adoption among neurosurgeons in training is a "follow the leader" phenomenon, wherein new surgeons tend to adopt the technology used during residency. In neurosurgery today, robots are limited to computers functioning between the surgeon and patient. Their functions are confined to establishing a trajectory for navigation, with task execution solely in the surgeon's hands. In this review, the authors discuss significant untapped technologies waiting to be used for more meaningful applications. They explore the history and current manifestations of various modern technologies, and project what innovations may lie ahead.

Single-stage cranioplasty with customized polyetheretherketone implant after tumor resection using virtual reality and augmented reality for precise implant customization and placement: illustrative case.

BACKGROUND: Cranioplasties are routinely performed to restore cosmesis and to protect intracranial contents after trauma, resection of tumors, or other pathologies. Traditionally done as a second-stage procedure, new single-stage cranioplasty protocols have been developed to minimize recovery periods, decrease complications, and improve patient satisfaction. These protocols, however, still require the use of larger than planned implants or use larger than ideal incisions to accommodate three-dimensional (3D) templates, which may not be optimal in regions with complex bony anatomy. OBSERVATIONS: A 50-year-old woman with a painful and progressively enlarging hemangioma of the left frontal bone underwent a single-stage resection followed by custom cranioplasty using a new extended reality (XR)-based workflow. Excellent cosmetic results, decreased operative time, and a feasible workflow were achieved. LESSONS: The use of an XR-based visualization platform allows the surgeon to treat lesions and perform custom cranioplasties in one session while avoiding common pitfalls of current single-stage workflows, such as increased operative times for tailoring implants, as well as minimizing the use of 3D overlay models, which may not appropriately conform to complex regional bony anatomy intraoperatively.

Augmented reality-assisted microsurgical resection of brain arteriovenous malformations: illustrative case.

BACKGROUND: Arteriovenous malformations (AVMs) of the brain are vessel conglomerates of feeding arteries and draining veins that carry a risk of spontaneous and intraoperative rupture. Augmented reality (AR)-assisted neuronavigation permits continuous, real-time, updated visualization of navigation information through a heads-up display, thereby potentially improving the safety of surgical resection of AVMs. OBSERVATIONS: The authors report a case of a 37-year-old female presenting with a 2-year history of recurrent falls due to intermittent right-sided weakness and increasing clumsiness in the right upper extremity. Magnetic resonance imaging, magnetic resonance angiography, and cerebral angiography of the brain revealed a left parietal Spetzler-Martin grade III AVM. After endovascular embolization of the AVM, microsurgical resection using an AR-assisted neuronavigation system was performed. Postoperative angiography confirmed complete obliteration of arteriovenous shunting. The postsurgical course was unremarkable, and the patient remains in excellent health. LESSONS: Our case describes the operative setup and intraoperative employment of AR-assisted neuronavigation for AVM resection. Application of this technology may improve workflow and enhance patient safety.

Percutaneous placement of lumbar pedicle screws via intraoperative CT image-based augmented reality-guided technology.

OBJECTIVE: The authors aimed to assess, in a bone-agar experimental setting, the feasibility and accuracy of percutaneous lumbar pedicle screw placements using an intraoperative CT image-based augmented reality (AR)-guided method compared to placements using a radiograph-guided method. They also compared two AR hologram alignment methods. METHODS: Twelve lumbar spine sawbones were completely embedded in hardened opaque agar, and a cubic marker was fixed on each phantom. After intraoperative CT, a 3D model of each phantom was generated, and a specialized application was deployed into an AR headset (Microsoft HoloLens). One hundred twenty pedicle screws, simulated by Kirschner wires (K-wires), were placed by two experienced surgeons, who each placed a total of 60 screws: 20 placed with a radiograph-guided technique, 20 with an AR technique in which the hologram was manually aligned, and 20 with an AR technique in which the hologram was automatically aligned. For each K-wire, the insertion path was expanded to a 6.5-mm diameter to simulate a lumbar pedicle screw. CT imaging of each phantom was performed after all K-wire placements, and the operative time required for each K-wire placement was recorded. An independent radiologist rated all images of K-wire placements. Outcomes were classified as grade I (no pedicle perforation), grade II (screw perforation of the cortex by up to 2 mm), or grade III (screw perforation of the cortex by > 2 mm). In a clinical situation, placements scored as grade I or II would be acceptable and safe for patients. RESULTS: Among all screw placements, 75 (94%) of 80 AR-guided placements and 40 (100%) of 40 radiograph-guided placements were acceptable (i.e., grade I or II; p = 0.106). Radiograph-guided placements had more grade I outcomes than the AR-guided method (p < 0.0001). The accuracy of the two AR alignment methods (p = 0.526) was not statistically significantly different, and neither was it different between the AR and radiograph groups (p < 0.0001). AR-guided placements required less time than the radiograph-guided placements (mean ± standard deviation, 131.76 ± 24.57 vs 181.43 ± 15.82 seconds, p < 0.0001). Placements performed using the automatic-alignment method required less time than those using the manual-alignment method (124.20 ± 23.80 vs 139.33 ± 23.21 seconds, p = 0.0081). CONCLUSIONS: In bone-agar experimental settings, AR-guided percutaneous lumbar pedicle screw placements were acceptable and more efficient than radiograph-guided placements. In a comparison of the two AR-guided placements, the automatic-alignment method was as accurate as the manual method but more efficient. Because of some limitations, the AR-guided system cannot be recommended in a clinical setting until there is significant improvement of this technology.